Instructions to use macmacmacmac/CLEF-Screen-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use macmacmacmac/CLEF-Screen-V2 with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Publish the counted chart. Card text and png only. Weights unchanged.
Browse files- README.md +1 -1
- jev_human_questions_chart.png +2 -2
README.md
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Checked 2026-11-05 against the live run3 counts and the per-row score files. Q1 row 2 is stop replay at 0.99: 51/249 tasks finished, 7/249 hijacked, 35/37 normal tasks passed, adaptive 53/100. The judge normal rate is 141/148. No per-check timing is on the chart. CLEF-Screen caught 20098/20271 (99.1%). `build_replication_package.py` rerun matched the published AUCs. Two gaps stay labeled: CLEF-DualScreen has no local per-row test file, and the SecJev redo numbers are bench draws.
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jev_human_questions_chart.png
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Git LFS Details
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Git LFS Details
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